Abstract

The Snowy Precipitation Enhancement Research Project (SPERP) was undertaken in winters from May 2005 to June 2009 in the Snowy Mountains region of southeastern Australia. Part I of this paper describes the design and implementation of the project, as well as the characteristics of the key datasets collected during the field phase. The primary analysis in this paper (Part II) shows an unequivocal impact on the targeting of seeding material, with the maximum level of silver in snow samples collected from the primary target area found to be significantly greater in seeded than unseeded experimental units (EUs). A positive but not statistically significant impact on precipitation was found. Further analysis shows that a substantial source of uncertainty in the estimation of the impacts of seeding on precipitation is associated with EUs where the seeding generators operated for relatively few hours. When the analysis is repeated using only EUs with more than 45 generator hours, the increase in precipitation in the primary target area is 14% at the 8% significance level. When applying that analysis to the overall target area, the precipitation increase is 14% at the 3% significance level. A secondary analysis of the ratio of silver to indium in snow supports the hypothesis that seeding material affected the cloud microphysics. Other secondary analyses reveal that seeding had an impact on virtually all of the physical variables examined in a manner consistent with the seeding hypothesis.

Abstract

Over 50 satellite rainfall algorithms were evaluated for a 5° square region in the equatorial western Pacific Ocean during TOGA COARE, November 1992–February 1993. These satellite algorithms used GMS VIS/IR, AVHRR, and SSM/I data to estimate rainfall on both instantaneous and monthly timescales. Validation data came from two calibrated shipboard Doppler radars measuring rainfall every 10 min.

There was large variation among algorithms in the magnitude of the satellite-estimated rainfall, but the patterns of rainfall were similar among algorithm types. Compared to the radar observations, most of the satellite algorithms overestimated the amount of rain falling in the region, typically by about 30%. Patterns of monthly observed rainfall were well represented by the satellite algorithms, with correlation coefficients with the observations ranging from 0.86 to 0.90 for algorithms using geostationary data and 0.69 to 0.86 for AVHRR and SSM/I algorithms when validated on a 0.5° grid. Patterns of instantaneous rain rates were also well analyzed, with correlation coefficients with the radar observations of 0.43–0.58 for the geostationary algorithms and 0.60–0.78 for SSM/I algorithms.

Two case studies are presented to demonstrate the capability of one IR algorithm and three microwave algorithms to estimate instantaneous rainfall rates in the Tropics. The three microwave algorithms differed in their estimates of rain area but all showed greater ability than the IR algorithm to reproduce the spatial pattern of rainfall.

Abstract

Two anomalies are described which arise in the kernel for stochastic droplet collection when it is specified by the formula of Scott and Chen for the linear collision efficiency y(R,r) and by the formula of Wobus et al. for the droplet terminal velocity V(R). It is pointed out that if accurate values for y(R,r) are to be obtained for a given droplet pair by interpolation using data for specific droplet pairs, then for large droplet radii (R<30 μm) it is desirable that these data he tabulated for 2-μm intervals of R. It is shown that if the difference in terminal velocities of two droplets is computed from a formula approximating V(R) and composed of various functions V*(R) applicable over adjoining domains of R, then it is necessary that these functions be constructed so that the formula and its derivatives, at least up to second order, are everywhere continuous. An improved formula for V(R) satisfying this criterion is described.

Abstract

Variability in the wet season of tropical northern Australia is examined over its main months, November–March, with a focus on zonal differences between the western, central, and eastern domains, which encompass the northern parts of Western Australia, Northern Territory, and Queensland, respectively. The seasonal progression of the wet season is similar across the region, with steadily increasing atmospheric moisture and rainfall into the core months of the monsoon, January and February, decreasing into March. This seasonal progression differs in the eastern domain, where there is an extension of premonsoonal conditions into December, and a delay of the onset of the monsoon until January. An analysis of TRMM precipitation features (PFs) reveals more intense convection during the premonsoon, steadily decreasing in intensity to much shallower convection by March, with a steady increase in the overall number of PFs throughout the wet season. Regionally, the intensity of PFs steadily decreases eastward across northern Australia with significantly weaker, shallower PFs over the eastern domain. Intraseasonal variability associated with the Madden–Julian oscillation (MJO) has a consistent impact on the rainfall and the total number of TRMM PFs across northern Australia, with both increasing and decreasing during the active and suppressed phases, respectively. However, regional variations in the effect of the MJO lead to radically different characteristics of PFs during the suppressed phases; intense convection and thunderstorms become more frequent over the western and central domains, while shallow PFs associated with the warm rain precipitation process increase in number over the eastern domain.

Abstract

The representation of the marine boundary layer (BL) clouds remains a formidable challenge for state-of-the-art simulations. A recent study by Bodas-Salcedo et al. using the Met Office Unified Model highlights that the underprediction of the low/midlevel postfrontal clouds contributes to the largest bias of the surface downwelling shortwave radiation over the Southern Ocean (SO). A-Train observations and limited in situ measurements have been used to evaluate the Weather Research and Forecasting Model, version 3.3.1 (WRFV3.3.1), in simulating the postfrontal clouds over Tasmania and the SO. The simulated cloud macro/microphysical properties are compared against the observations. Experiments are also undertaken to test the sensitivity of model resolution, microphysical (MP) schemes, planetary boundary layer (PBL) schemes, and cloud condensation nuclei (CCN) concentration. The simulations demonstrate a considerable level of skill in representing the clouds during the frontal passages and, to a lesser extent, in the postfrontal environment. The simulations, however, have great difficulties in portraying the widespread marine BL clouds that are not immediately associated with fronts. This shortcoming is persistent to the changes of model configuration and physical parameterization. The representation of large-scale conditions and their connections with the BL clouds are discussed. A lack of BL moisture is the most obvious explanation for the shortcoming, which may be a consequence of either strong entrainment or weak surface fluxes. It is speculated that the BL wind shear/turbulence may be an issue over the SO. More comprehensive observations are necessary to fully investigate the deficiency of the simulations.

Abstract

The relationship between orographic precipitation, low-level thermodynamic stability, and the synoptic meteorology is explored for the Snowy Mountains of southeast Australia. A 21-yr dataset (May–October, 1995–2015) of upper-air soundings from an upwind site is used to define synoptic indicators and the low-level stability. A K-means clustering algorithm was employed to classify the daily meteorology into four synoptic classes. The initial classification, based only on six synoptic indicators, distinctly defines both the surface precipitation and the low-level stability by class. Consistent with theory, the wet classes are found to have weak low-level stability, and the dry classes have strong low-level stability. By including low-level stability as an additional input variable to the clustering method, statistically significant correlations were found between the precipitation and the low-level stability within each of the four classes. An examination of the joint PDF reveals a highly nonlinear relationship; heavy rain was associated with very weak low-level stability, and conversely, strong low-level stability was associated with very little precipitation. Building on these historical relationships, model output statistics (MOS) from a moderate resolution (12-km spatial resolution) operational forecast were used to develop stepwise regression models designed to improve the 24-h forecast of precipitation over the Snowy Mountains. A single regression model for all days was found to reduce the RMSE by 7% and the bias by 75%. A class-based regression model was found to reduce the overall RMSE by 30% and the bias by 85%.

Abstract

A “climatology” of supercooled cloud tops is presented for southeastern Australia and the western United States, where historic glaciogenic cloud-seeding trials have been located. The climatology finds that supercooled cloud tops are common over the mountainous region of southeastern Australia and Tasmania (SEAT). Regions where cloud-seeding trials reported positive results coincide with a higher likelihood of observing supercooled cloud tops. Maximum absolute frequencies (AFs) occur ∼40% of the time during winter. There is a relationship between the underlying orography and the likelihood of observing supercooled liquid water (SLW)-topped clouds. Regions of the United States that have been the subject of cloud-seeding trials show lower AFs of SLW-topped clouds. The maximum is located over the Sierra Nevada and occurs ∼20% of the time during winter (Sierra Cooperative Pilot Project). These sites are on mountains with peaks higher than any found in SEAT (>3000 m). For the Sierra Nevada, the AF of SLW-topped clouds decreases as the elevation increases, with glaciation occurring at the higher elevations. The remote sensing of supercooled cloud tops is not proof of a region’s amenability for glaciogenic cloud seeding. This study simply highlights the significant environmental differences between historical cloud-seeding regions in the United States and Australia, suggesting that it is not reasonable to extrapolate results from one region to another. Without in situ cloud microphysical measurements, in-depth knowledge of the timing and duration of potentially seedable events, or knowledge of the synoptic forcing of such events, it is not possible to categorize a region’s potential for precipitation augmentation operations.

Abstract

Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 observations from the Terra satellite are used to create a 3-yr climatology of cloud-top phase over a section of the Southern Ocean (south of Australia) and the North Pacific Ocean. The intent is to highlight the extensive presence of supercooled liquid water over the Southern Ocean region, particularly during summer. The phase of such clouds directly affects the absorbed shortwave radiation, which has recently been found to be “poorly simulated in both state-of-the-art reanalysis and coupled global climate models” (Trenberth and Fasullo).

The climatology finds that supercooled liquid water is present year-round in the low-altitude clouds across this section of the Southern Ocean. Further, the MODIS cloud phase algorithm identifies very few glaciated cloud tops at temperatures above −20°C, rather inferring a large portion of “uncertain” cloud tops. Between 50° and 60°S during the summer, the albedo effect is compounded by a seasonal reduction in high-level cirrus. This is in direct contrast to the Bering Sea and Gulf of Alaska. Here MODIS finds a higher likelihood of observing warm liquid water clouds during summer and a reduction in the relative frequency of cloud tops within the 0° to −20°C temperature range.

As the MODIS cloud phase product has limited ability to confidently identify cloud-top phase between −5° and −25°C, future research should include observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and other space-based sensors to help with the classification within this temperature range. Further, multiregion in situ verification of any remotely sensed observations is vital to further understanding the cloud phase processes.

Abstract

Cloud and precipitation properties of the midlatitude storm-track regions over the Southern Ocean (SO) and North Atlantic (NA) are explored using reanalysis datasets and A-Train observations from 2007 to 2011. In addition to the high-level retrieval products, lower-level observed variables—CloudSat radar reflectivity and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar attenuated backscatter—are directly examined using both contoured frequency by altitude diagrams (CFADs) and contoured frequency by temperature diagrams (CFTDs) to provide direct insight into thermodynamic phase properties. While the wintertime temperature profiles are similar over the two regions, the summertime environment is warmer over the NA. The NA atmosphere is generally moister than the SO, while the SO boundary layer is moister during winter. The results herein suggest that although the two regions exhibit many similarities in the prevalence of boundary layer clouds (BLCs) and frontal systems, notable differences exist. The NA environment exhibits stronger seasonality in thermodynamic structure, cloud, and precipitation properties than the SO. The regional differences of cloud properties are dominated by microphysics in winter and thermodynamics in summer. Glaciated clouds with higher reflectivities are found at warmer temperatures over the NA. BLCs (primarily below 1.5 km) are a predominant component over the SO. The wintertime boundary layer is shallower over the SO. Midlevel clouds consisting of smaller hydrometeors in higher concentration (potentially supercooled liquid water) are more frequently observed over the SO. Cirrus clouds are more prevalent over the NA. Notable differences exist in both the frequencies of thermodynamic phases of precipitation and intensity of warm rain over the two regions.

Abstract

Data from a precipitation gauge network in the Snowy Mountains of southeastern Australia have been analyzed to produce a new climatology of wintertime precipitation and airmass history for the region in the period 1990–2009. Precipitation amounts on the western slopes and in the high elevations (>1000 m) of the Snowy Mountains region have experienced a decline in precipitation in excess of the general decline in southeastern Australia. The contrast in the decline east and west of the ranges suggests that factors influencing orographic precipitation are of particular importance. A synoptic decomposition of precipitation events has been performed, which demonstrates that about 57% of the wintertime precipitation may be attributed to storms associated with “cutoff lows” (equatorward of 45°S). A further 40% was found to be due to “embedded lows,” with the remainder due to Australian east coast lows and several other sporadically occurring events. The declining trend in wintertime precipitation over the past two decades is most clearly seen in the intensity of precipitation due to cutoff lows and coincides with a decline in the number of systems associated with a cold frontal passage. Airmass history during precipitation events was represented by back trajectories calculated from ECMWF Interim Reanalysis data, and statistics of air parcel position were related to observations of precipitation intensity. This approach gives insight into sources of moisture during wintertime storms, identifying “moisture corridors,” which are typically important for transport of water vapor from remote sources to the Snowy Mountains region. The prevalence of these moisture corridors is associated with the southern annular mode, which corresponds to fluctuations in the strength of the westerly winds in southeastern Australia.